1. Field of the Invention
The present invention is related to valuating hydrocarbon reservoirs and more particularly to automatically selecting known analogous reservoirs for valuating newly identified hydrocarbon reservoirs.
2. Background Description
Each new hydrocarbon reservoir has an inherent total value that is based on unknown properties. In particular, the inherent value depends on the total amount of material that is ultimately recoverable from the reservoir (production potential) and the cost of recovering the material or capture difficulty. Until the material is actually recovered, those unknown properties remain unknown and the inherent value can only be estimated. Previously to estimate value, one or more experts first identified and selected existing reservoirs with certain similar aspects to the new reservoir, known as “analogous reservoirs.” The expert(s) used the selected analogous reservoirs to estimate the value of the new reservoir. A mis-valuation could lead to wasted resources, e.g., from passing on an undervalued reservoir to exploit an overvalued reservoir. So, to minimize errors, the trend has been to less reliance on subjective, expert judgment for subjectively selecting analogous reservoirs, and in turn, towards more objective selection approaches. For example, similarity functions have been used in valuing new hydrocarbon reservoirs.
Similarity functions have found many uses in the art today for comparing members of a collection of objects, or population, and selecting those objects that, although they not identical, are recognizably similar. A typical state of the art approach to determining similarity function parameters applies expert knowledge and/or local search methods, such as gradient descent and genetic algorithms. Generally, a common problem with these approaches is continued reliance on subjective judgment without necessarily arriving at the most similar matches.
A typical state of the art approach uses available reservoir information collected in a reservoir database and a similarity function to automate identifying and selecting analogous reservoirs. However, an expert (or experts) still chooses exact properties and weights used in the similarity function to compare any known properties of a target (new) reservoir with the properties of known reservoirs. Examples of manually specified (e.g., by experts specifying weights and/or properties) similarity functions selecting analogous reservoirs for estimating value are provided, for example, by published U.S. Patent Application No. 2011/0118983, “System and Method for Reservoir Analysis Background” to Rowan; and by Bhushan et al., “A Novel Approach to Identify Reservoir Analogues,” Shell International Exploration and Production, 2002.
Hopefully, the expert chooses the best properties and weights to identify reservoirs with properties most similar to the target reservoir as analogous. Although this has automated identifying the final selection, it is still somewhat subjective because experts still choose the properties and weights. Consequently, selecting the best properties and weights is still subjective and makes selecting analogous reservoirs a difficult and error-prone task.
Thus, there is a need for improved application of similarity functions to comparing one object with other analogous objects from a population of similar objects; and, more particularly for automatically weighting similarity functions for selecting existing hydrocarbon reservoirs as analogous for valuating new reservoirs.